Pandas Profiling Report

Dataset statistics

Number of variables	9
Number of observations	768
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	54.1 KiB
Average record size in memory	72.2 B

Variable types

Numeric	8
Categorical	1

Alerts

`Pregnancies` is highly correlated with `Age`	High correlation
`Glucose` is highly correlated with `Insulin`	High correlation
`SkinThickness` is highly correlated with `BMI`	High correlation
`Insulin` is highly correlated with `Glucose` and 1 other fields	High correlation
`BMI` is highly correlated with `SkinThickness`	High correlation
`Age` is highly correlated with `Pregnancies`	High correlation
`Outcome` is highly correlated with `Insulin`	High correlation
`Pregnancies` is highly correlated with `Age`	High correlation
`SkinThickness` is highly correlated with `BMI`	High correlation
`BMI` is highly correlated with `SkinThickness`	High correlation
`Age` is highly correlated with `Pregnancies`	High correlation
`Pregnancies` is highly correlated with `Age`	High correlation
`Glucose` is highly correlated with `Insulin` and 1 other fields	High correlation
`BloodPressure` is highly correlated with `BMI`	High correlation
`SkinThickness` is highly correlated with `BMI`	High correlation
`Insulin` is highly correlated with `Glucose`	High correlation
`BMI` is highly correlated with `BloodPressure` and 2 other fields	High correlation
`DiabetesPedigreeFunction` is highly correlated with `BMI`	High correlation
`Age` is highly correlated with `Pregnancies`	High correlation
`Outcome` is highly correlated with `Glucose`	High correlation
`Pregnancies` has 111 (14.5%) zeros	Zeros

Reproduction

Analysis started	2023-02-14 11:42:53.630328
Analysis finished	2023-02-14 11:43:01.447597
Duration	7.82 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Pregnancies
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	17
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.845052083

Minimum	0
Maximum	17
Zeros	111
Zeros (%)	14.5%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	3
Q3	6
95-th percentile	10
Maximum	17
Range	17
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.369578063
Coefficient of variation (CV)	0.8763413316
Kurtosis	0.1592197775
Mean	3.845052083
Median Absolute Deviation (MAD)	2
Skewness	0.9016739792
Sum	2953
Variance	11.35405632
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	135	17.6%
0	111	14.5%
2	103	13.4%
3	75	9.8%
4	68	8.9%
5	57	7.4%
6	50	6.5%
7	45	5.9%
8	38	4.9%
9	28	3.6%
Other values (7)	58	7.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	111	14.5%
1	135	17.6%
2	103	13.4%
3	75	9.8%
4	68	8.9%
5	57	7.4%
6	50	6.5%
7	45	5.9%
8	38	4.9%
9	28	3.6%

Value	Count	Frequency (%)
17	1	0.1%
15	1	0.1%
14	2	0.3%
13	10	1.3%
12	9	1.2%
11	11	1.4%
10	24	3.1%
9	28	3.6%
8	38	4.9%
7	45	5.9%

Glucose
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	135
Distinct (%)	17.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	121.6770833

Minimum	44
Maximum	199
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	44
5-th percentile	80
Q1	99.75
median	117
Q3	140.25
95-th percentile	181
Maximum	199
Range	155
Interquartile range (IQR)	40.5

Descriptive statistics

Standard deviation	30.46416059
Coefficient of variation (CV)	0.2503689253
Kurtosis	-0.2681052005
Mean	121.6770833
Median Absolute Deviation (MAD)	20
Skewness	0.532324244
Sum	93448
Variance	928.0650804
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
99	17	2.2%
100	17	2.2%
125	14	1.8%
111	14	1.8%
106	14	1.8%
107	14	1.8%
129	14	1.8%
105	13	1.7%
112	13	1.7%
95	13	1.7%
Other values (125)	625	81.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
44	1	0.1%
56	1	0.1%
57	2	0.3%
61	1	0.1%
62	1	0.1%
65	1	0.1%
67	1	0.1%
68	3	0.4%
71	4	0.5%
72	1	0.1%

Value	Count	Frequency (%)
199	1	0.1%
198	1	0.1%
197	4	0.5%
196	3	0.4%
195	2	0.3%
194	3	0.4%
193	2	0.3%
191	1	0.1%
190	1	0.1%
189	4	0.5%

BloodPressure
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	47
Distinct (%)	6.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	72.38932292

Minimum	24
Maximum	122
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	24
5-th percentile	52
Q1	64
median	72
Q3	80
95-th percentile	90
Maximum	122
Range	98
Interquartile range (IQR)	16

Descriptive statistics

Standard deviation	12.10603912
Coefficient of variation (CV)	0.1672351478
Kurtosis	1.085427234
Mean	72.38932292
Median Absolute Deviation (MAD)	8
Skewness	0.1408302608
Sum	55595
Variance	146.5561831
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
70	76	9.9%
74	52	6.8%
78	45	5.9%
68	45	5.9%
72	44	5.7%
64	43	5.6%
80	40	5.2%
76	39	5.1%
60	37	4.8%
62	34	4.4%
Other values (37)	313	40.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
24	1	0.1%
30	2	0.3%
38	1	0.1%
40	1	0.1%
44	4	0.5%
46	2	0.3%
48	5	0.7%
50	13	1.7%
52	11	1.4%
54	11	1.4%

Value	Count	Frequency (%)
122	1	0.1%
114	1	0.1%
110	3	0.4%
108	2	0.3%
106	3	0.4%
104	2	0.3%
102	1	0.1%
100	3	0.4%
98	3	0.4%
96	4	0.5%

SkinThickness
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	50
Distinct (%)	6.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	29.08984375

Minimum	7
Maximum	99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	7
5-th percentile	14.35
Q1	25
median	28
Q3	32
95-th percentile	44
Maximum	99
Range	92
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	8.890819781
Coefficient of variation (CV)	0.3056331226
Kurtosis	5.067565126
Mean	29.08984375
Median Absolute Deviation (MAD)	4
Skewness	0.8174770535
Sum	22341
Variance	79.04667638
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
27	162	21.1%
32	119	15.5%
30	27	3.5%
23	22	2.9%
28	20	2.6%
33	20	2.6%
18	20	2.6%
31	19	2.5%
19	18	2.3%
39	18	2.3%
Other values (40)	323	42.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
7	2	0.3%
8	2	0.3%
10	5	0.7%
11	6	0.8%
12	7	0.9%
13	11	1.4%
14	6	0.8%
15	14	1.8%
16	6	0.8%
17	14	1.8%

Value	Count	Frequency (%)
99	1	0.1%
63	1	0.1%
60	1	0.1%
56	1	0.1%
54	2	0.3%
52	2	0.3%
51	1	0.1%
50	3	0.4%
49	3	0.4%
48	4	0.5%

Insulin
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	187
Distinct (%)	24.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	141.7539062

Minimum	14
Maximum	846
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	14
5-th percentile	50
Q1	102.5
median	102.5
Q3	169.5
95-th percentile	293
Maximum	846
Range	832
Interquartile range (IQR)	67

Descriptive statistics

Standard deviation	89.10084664
Coefficient of variation (CV)	0.6285600799
Kurtosis	13.85295067
Mean	141.7539062
Median Absolute Deviation (MAD)	36.5
Skewness	3.028046221
Sum	108867
Variance	7938.960871
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
102.5	236	30.7%
169.5	138	18.0%
105	11	1.4%
130	9	1.2%
140	9	1.2%
120	8	1.0%
94	7	0.9%
180	7	0.9%
100	7	0.9%
135	6	0.8%
Other values (177)	330	43.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
14	1	0.1%
15	1	0.1%
16	1	0.1%
18	2	0.3%
22	1	0.1%
23	2	0.3%
25	1	0.1%
29	1	0.1%
32	1	0.1%
36	3	0.4%

Value	Count	Frequency (%)
846	1	0.1%
744	1	0.1%
680	1	0.1%
600	1	0.1%
579	1	0.1%
545	1	0.1%
543	1	0.1%
540	1	0.1%
510	1	0.1%
495	2	0.3%

BMI
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	247
Distinct (%)	32.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	32.43463542

Minimum	18.2
Maximum	67.1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	18.2
5-th percentile	22.235
Q1	27.5
median	32.05
Q3	36.6
95-th percentile	44.395
Maximum	67.1
Range	48.9
Interquartile range (IQR)	9.1

Descriptive statistics

Standard deviation	6.880497797
Coefficient of variation (CV)	0.2121342728
Kurtosis	0.9154853269
Mean	32.43463542
Median Absolute Deviation (MAD)	4.55
Skewness	0.6064156081
Sum	24909.8
Variance	47.34124993
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
30.1	18	2.3%
32	13	1.7%
31.2	12	1.6%
31.6	12	1.6%
32.4	10	1.3%
33.3	10	1.3%
32.8	9	1.2%
32.9	9	1.2%
30.8	9	1.2%
29.7	8	1.0%
Other values (237)	658	85.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18.2	3	0.4%
18.4	1	0.1%
19.1	1	0.1%
19.3	1	0.1%
19.4	1	0.1%
19.5	2	0.3%
19.6	3	0.4%
19.9	1	0.1%
20	1	0.1%
20.1	1	0.1%

Value	Count	Frequency (%)
67.1	1	0.1%
59.4	1	0.1%
57.3	1	0.1%
55	1	0.1%
53.2	1	0.1%
52.9	1	0.1%
52.3	2	0.3%
50	1	0.1%
49.7	1	0.1%
49.6	1	0.1%

DiabetesPedigreeFunction
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	517
Distinct (%)	67.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4718763021

Minimum	0.078
Maximum	2.42
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	0.078
5-th percentile	0.14035
Q1	0.24375
median	0.3725
Q3	0.62625
95-th percentile	1.13285
Maximum	2.42
Range	2.342
Interquartile range (IQR)	0.3825

Descriptive statistics

Standard deviation	0.331328595
Coefficient of variation (CV)	0.7021513764
Kurtosis	5.594953528
Mean	0.4718763021
Median Absolute Deviation (MAD)	0.1675
Skewness	1.919911066
Sum	362.401
Variance	0.1097786379
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.258	6	0.8%
0.254	6	0.8%
0.268	5	0.7%
0.207	5	0.7%
0.261	5	0.7%
0.259	5	0.7%
0.238	5	0.7%
0.19	4	0.5%
0.263	4	0.5%
0.299	4	0.5%
Other values (507)	719	93.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.078	1	0.1%
0.084	1	0.1%
0.085	2	0.3%
0.088	2	0.3%
0.089	1	0.1%
0.092	1	0.1%
0.096	1	0.1%
0.1	1	0.1%
0.101	1	0.1%
0.102	1	0.1%

Value	Count	Frequency (%)
2.42	1	0.1%
2.329	1	0.1%
2.288	1	0.1%
2.137	1	0.1%
1.893	1	0.1%
1.781	1	0.1%
1.731	1	0.1%
1.699	1	0.1%
1.698	1	0.1%
1.6	1	0.1%

Age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	52
Distinct (%)	6.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	33.24088542

Minimum	21
Maximum	81
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.1 KiB

Quantile statistics

Minimum	21
5-th percentile	21
Q1	24
median	29
Q3	41
95-th percentile	58
Maximum	81
Range	60
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	11.76023154
Coefficient of variation (CV)	0.3537881556
Kurtosis	0.6431588885
Mean	33.24088542
Median Absolute Deviation (MAD)	7
Skewness	1.129596701
Sum	25529
Variance	138.3030459
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	72	9.4%
21	63	8.2%
25	48	6.2%
24	46	6.0%
23	38	4.9%
28	35	4.6%
26	33	4.3%
27	32	4.2%
29	29	3.8%
31	24	3.1%
Other values (42)	348	45.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	63	8.2%
22	72	9.4%
23	38	4.9%
24	46	6.0%
25	48	6.2%
26	33	4.3%
27	32	4.2%
28	35	4.6%
29	29	3.8%
30	21	2.7%

Value	Count	Frequency (%)
81	1	0.1%
72	1	0.1%
70	1	0.1%
69	2	0.3%
68	1	0.1%
67	3	0.4%
66	4	0.5%
65	3	0.4%
64	1	0.1%
63	4	0.5%

Outcome
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	6.1 KiB

0	500
1	268

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
0	6	148.0	72.0	35.0	169.5	33.6	0.627	50	1
1	1	85.0	66.0	29.0	102.5	26.6	0.351	31	0
2	8	183.0	64.0	32.0	169.5	23.3	0.672	32	1
3	1	89.0	66.0	23.0	94.0	28.1	0.167	21	0
4	0	137.0	40.0	35.0	168.0	43.1	2.288	33	1
5	5	116.0	74.0	27.0	102.5	25.6	0.201	30	0
6	3	78.0	50.0	32.0	88.0	31.0	0.248	26	1
7	10	115.0	70.0	27.0	102.5	35.3	0.134	29	0
8	2	197.0	70.0	45.0	543.0	30.5	0.158	53	1
9	8	125.0	96.0	32.0	169.5	34.3	0.232	54	1

Last rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
758	1	106.0	76.0	27.0	102.5	37.5	0.197	26	0
759	6	190.0	92.0	32.0	169.5	35.5	0.278	66	1
760	2	88.0	58.0	26.0	16.0	28.4	0.766	22	0
761	9	170.0	74.0	31.0	169.5	44.0	0.403	43	1
762	9	89.0	62.0	27.0	102.5	22.5	0.142	33	0
763	10	101.0	76.0	48.0	180.0	32.9	0.171	63	0
764	2	122.0	70.0	27.0	102.5	36.8	0.340	27	0
765	5	121.0	72.0	23.0	112.0	26.2	0.245	30	0
766	1	126.0	60.0	32.0	169.5	30.1	0.349	47	1
767	1	93.0	70.0	31.0	102.5	30.4	0.315	23	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows